Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field.
By Lingle Wang, Yujie Wu, Yuqing Deng, Byungchan Kim, Levi Pierce, Goran Krilov, Dmitry Lupyan, S. Robinson, Markus K. Dahlgren, Jeremy R. Greenwood and 19 more. 2015
1,186 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- David L. Mobley
- Izhar Wallach
- Michael K. Gilson
- Junmei Wang
- David E. Shaw
- Michael Dzamba
- Abraham Heifets
- Abhinav Vishnu
In Materials Chemistry
- Junmei Wang
- David L. Mobley
- Ken A. Dill
- Izhar Wallach
- David E. Shaw
- John D. Chodera
- Michael Dzamba
- Carlos Simmerling
In Molecular Biology
- David L. Mobley
- Ken A. Dill
- Michael K. Gilson
- Junmei Wang
- Emiliano Brini
- Carlos Simmerling
- Izhar Wallach
- David E. Shaw
Citations in the corpus
- AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery (2015, background): “The ability to accurately predict molecular binding would reduce the time-to-discovery of new treatments, help eliminate toxic molecules early in development, and guide medicinal chemistry efforts [1, 2].”
- How does a small molecule bind at a cryptic binding site? (2021, methodology): “7 power, the development of new sampling methodology, and improvements in force field accuracy, the accuracy of FEP calculation of ligand-binding free energy has improved substantially in recent years.(31) We calculated using FEP(32) the binding free energies of various stable IL2 binding poses adop”
- Best practices for constructing, preparing, and evaluating protein-ligand binding affinity benchmarks [Article v0.2] (2021, background): “An early influential publication from Schrödinger [20] reported mean unsigned errors of 1.2 kcal/mol on a curated set of 8 protein targets, 199 ligands, and 330 perturbations using their commercial implementation of FEP.”
- Fast Identification of Possible Drug Treatment of Coronavirus Disease −19 (COVID-19) Through Computational Drug Repurposing Study (2020, background): “…such as the endpoint MM-PB/GBSA (molecular mechanics-Poisson Boltzmann/ Generalized Born Surface Area) methods 2, 3, 8-21 and the alchemical thermodynamic integration (TI) and free energy perturbation (FEP) methods, 22, 23 have been extensively applied in structure-based drug discovery projects.”